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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
id: string
labels: struct<eu_ai_act: struct<autonomy_level: string, risk_class: string>, fda: struct<autonomy_level: st (... 151 chars omitted)
child 0, eu_ai_act: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
child 1, fda: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
child 2, health_canada: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
child 3, mhra: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
metadata: struct<autonomy: string, clinical_task: string, condition_severity: string, intended_use: string, ou (... 67 chars omitted)
child 0, autonomy: string
child 1, clinical_task: string
child 2, condition_severity: string
child 3, intended_use: string
child 4, output_type: string
child 5, patient_facing: bool
child 6, tools: list<item: string>
child 0, item: string
stratum: string
pccp: null
deployed_fingerprint: struct<data: string, prompt: string, tools: string, weights: string>
child 0, data: string
child 1, prompt: string
child 2, tools: string
child 3, weights: string
true_out_of_envelope: bool
changed_components: list<item: string>
child 0, item: string
deltas: list<item: struct<component: string, magnitude: struct<est: double, true: double>>>
child 0, item: struct<component: string, magnitude: struct<est: double, true: double>>
child 0, component: string
child 1, magnitude: struct<est: double, true: double>
child 0, est: double
child 1, true: double
live_fingerprint: struct<data: string, prompt: string, tools: string, weights: string>
child 0, data: string
child 1, prompt: string
child 2, tools: string
child 3, weights: string
to
{'changed_components': List(Value('string')), 'deltas': List({'component': Value('string'), 'magnitude': {'est': Value('float64'), 'true': Value('float64')}}), 'deployed_fingerprint': {'data': Value('string'), 'prompt': Value('string'), 'tools': Value('string'), 'weights': Value('string')}, 'id': Value('string'), 'live_fingerprint': {'data': Value('string'), 'prompt': Value('string'), 'tools': Value('string'), 'weights': Value('string')}, 'pccp': {'allowed': List(Json(decode=True))}, 'true_out_of_envelope': Value('bool')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: string
labels: struct<eu_ai_act: struct<autonomy_level: string, risk_class: string>, fda: struct<autonomy_level: st (... 151 chars omitted)
child 0, eu_ai_act: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
child 1, fda: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
child 2, health_canada: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
child 3, mhra: struct<autonomy_level: string, risk_class: string>
child 0, autonomy_level: string
child 1, risk_class: string
metadata: struct<autonomy: string, clinical_task: string, condition_severity: string, intended_use: string, ou (... 67 chars omitted)
child 0, autonomy: string
child 1, clinical_task: string
child 2, condition_severity: string
child 3, intended_use: string
child 4, output_type: string
child 5, patient_facing: bool
child 6, tools: list<item: string>
child 0, item: string
stratum: string
pccp: null
deployed_fingerprint: struct<data: string, prompt: string, tools: string, weights: string>
child 0, data: string
child 1, prompt: string
child 2, tools: string
child 3, weights: string
true_out_of_envelope: bool
changed_components: list<item: string>
child 0, item: string
deltas: list<item: struct<component: string, magnitude: struct<est: double, true: double>>>
child 0, item: struct<component: string, magnitude: struct<est: double, true: double>>
child 0, component: string
child 1, magnitude: struct<est: double, true: double>
child 0, est: double
child 1, true: double
live_fingerprint: struct<data: string, prompt: string, tools: string, weights: string>
child 0, data: string
child 1, prompt: string
child 2, tools: string
child 3, weights: string
to
{'changed_components': List(Value('string')), 'deltas': List({'component': Value('string'), 'magnitude': {'est': Value('float64'), 'true': Value('float64')}}), 'deployed_fingerprint': {'data': Value('string'), 'prompt': Value('string'), 'tools': Value('string'), 'weights': Value('string')}, 'id': Value('string'), 'live_fingerprint': {'data': Value('string'), 'prompt': Value('string'), 'tools': Value('string'), 'weights': Value('string')}, 'pccp': {'allowed': List(Json(decode=True))}, 'true_out_of_envelope': Value('bool')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
changed_components list | deltas list | deployed_fingerprint dict | id string | live_fingerprint dict | pccp dict | true_out_of_envelope bool |
|---|---|---|---|---|---|---|
[
"tools"
] | [
{
"component": "tools",
"magnitude": null
}
] | {
"data": "41aa3a4e1a5102981a9cf542dc65023414a1d9c3d7826933186ba953076966b9",
"prompt": "98651dfef1fdff3b8b571b1880cf52840e205209bcb2dad5dc6ba6970bce9017",
"tools": "7c344d595da2252d5c06c8da74f161d528c01d875096453e03ffbbbb38cf6178",
"weights": "280e0b1c6c70e6f866f40a90ce424383d046c095a08c6013073f73a0ead19a18"
} | ch-0000 | {
"data": "41aa3a4e1a5102981a9cf542dc65023414a1d9c3d7826933186ba953076966b9",
"prompt": "98651dfef1fdff3b8b571b1880cf52840e205209bcb2dad5dc6ba6970bce9017",
"tools": "d788ad6c899999412b38c53908ebb8195cb6c18af0dd1ec760e992803717860a",
"weights": "280e0b1c6c70e6f866f40a90ce424383d046c095a08c6013073f73a0ead19a18"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"data",
"tools"
] | [
{
"component": "data",
"magnitude": null
},
{
"component": "tools",
"magnitude": null
}
] | {
"data": "a2d5450b3c6b4de3a67e7b7dbb0745541dd7c5cef3e727d6797d50f7e005d56a",
"prompt": "aa63ceec2d19ad03f252015fbc4a7fd78e6ba9d470db83ded1a34e46860995a1",
"tools": "aed03d08330bb53ec31ba7618c4e00acff5537f0e0150587b82b965c7b5ab337",
"weights": "6b896882729a45c2ed20b77d72ea805fb00e701f4a94825c4579a6d99efcda46"
} | ch-0001 | {
"data": "298235031872ce25c9d368f026d47ab26f6ff935a7f4f941a7fcfae88c63ad1d",
"prompt": "aa63ceec2d19ad03f252015fbc4a7fd78e6ba9d470db83ded1a34e46860995a1",
"tools": "e1a4a49572ade961dfb60fcb6ace070a4ff27b77364492b76874397864997f9f",
"weights": "6b896882729a45c2ed20b77d72ea805fb00e701f4a94825c4579a6d99efcda46"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"weights"
] | [
{
"component": "weights",
"magnitude": {
"est": 0,
"true": 0.0313
}
}
] | {
"data": "84019ec0555c3b2796c0c7991b4f1120f288a16b0fda819765a74d2cbb389931",
"prompt": "66998e97d1379e782851d3cfe6e1dc318c798d64eca06befdc1357a2f894ec0f",
"tools": "26a85a2a8eee446a5cf24ed55661814f34c9ae269930a3fd034871b49e95c545",
"weights": "e74b93979c30e53b8edd06a3db80578a44228f0f77544b5bed2db02370a4f3e0"
} | ch-0002 | {
"data": "84019ec0555c3b2796c0c7991b4f1120f288a16b0fda819765a74d2cbb389931",
"prompt": "66998e97d1379e782851d3cfe6e1dc318c798d64eca06befdc1357a2f894ec0f",
"tools": "26a85a2a8eee446a5cf24ed55661814f34c9ae269930a3fd034871b49e95c545",
"weights": "b5bbff3033b714e9df0c83004ad410ff2eaa384d27862f164988cb9126528eb9"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | false |
[
"weights"
] | [
{
"component": "weights",
"magnitude": {
"est": 0.0206,
"true": 0.0415
}
}
] | {
"data": "649c73e1fbab8050355efe7274a83ed8ba8a7a2af8461d06fb11e71b5b0a4483",
"prompt": "eb989b4a5b8952b9994d2745137d887450abfde7e686fcbf7e31a482323cf131",
"tools": "4dd294777e3e8ef9f4a1f37433f988f2324bd51c4ea69b88b5ed83b0bd2a4f9f",
"weights": "965cf461afa3819743808dea908df09b3dc76ecf67cc1e864f2531a88e9a160f"
} | ch-0003 | {
"data": "649c73e1fbab8050355efe7274a83ed8ba8a7a2af8461d06fb11e71b5b0a4483",
"prompt": "eb989b4a5b8952b9994d2745137d887450abfde7e686fcbf7e31a482323cf131",
"tools": "4dd294777e3e8ef9f4a1f37433f988f2324bd51c4ea69b88b5ed83b0bd2a4f9f",
"weights": "c6c243668dec0acce544032472be440332428265142848cfd02952ff341cc71c"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | false |
[
"data"
] | [
{
"component": "data",
"magnitude": null
}
] | {
"data": "eb9817d48fe42041a8536e339e314580da7106266d10a65f1f4ff5c6f4bf5597",
"prompt": "1d8128cc6ea9ccf8841a978b71c7201e07ea933e2e9e3c3dab985fded11d7704",
"tools": "a61a7fc5ab0da2795635fdddb47ed784b8c02198c25ece85f7e2505ab8685435",
"weights": "d50e542f6cf8a97a2b6ebbd019491c4030256359d8a6e46abe3d2a689832b4b3"
} | ch-0004 | {
"data": "e93278498549072e0695798793435a7d241378063573cb8611209364d12f949d",
"prompt": "1d8128cc6ea9ccf8841a978b71c7201e07ea933e2e9e3c3dab985fded11d7704",
"tools": "a61a7fc5ab0da2795635fdddb47ed784b8c02198c25ece85f7e2505ab8685435",
"weights": "d50e542f6cf8a97a2b6ebbd019491c4030256359d8a6e46abe3d2a689832b4b3"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"weights",
"prompt"
] | [
{
"component": "weights",
"magnitude": {
"est": 0.0382,
"true": 0.0228
}
},
{
"component": "prompt",
"magnitude": null
}
] | {
"data": "e2a5a801040806c302cbb5a96f6a8758b2b7288d71068a479377640d61bbd8bd",
"prompt": "316fe1622393f42d04d6884e8724ea3849b4fe81fd45fa8943a7be5c8a639561",
"tools": "ddcb6a9674cfc4ea226c04e39b3775f3be3255c4e02a4e30dd18bfa7ca82c957",
"weights": "3d467d96f4e7c88344bd2588c134a10ba11ad436c514538dd5cc18ed24856dfe"
} | ch-0005 | {
"data": "e2a5a801040806c302cbb5a96f6a8758b2b7288d71068a479377640d61bbd8bd",
"prompt": "bec8c2e31fa35248a85699c62edac8991bc3548f5f190298546f6d688891e15c",
"tools": "ddcb6a9674cfc4ea226c04e39b3775f3be3255c4e02a4e30dd18bfa7ca82c957",
"weights": "cf3a003f1a5bb293993e68f5c0b5b50b526f7d0e2d5dd487fd50088b3b1973be"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | false |
[
"prompt",
"data"
] | [
{
"component": "prompt",
"magnitude": null
},
{
"component": "data",
"magnitude": null
}
] | {
"data": "12adba685496798270c2c8f41c41fbe19866e1409053d1e191ba880601c5073a",
"prompt": "f71b43f1dfa0a641fcd5e8d9610cd96028c73e0646e2bd0af7feaf8befb9c977",
"tools": "ae8540f1997880ea791e454ca1de5c83423630b1da5fe1412825d92df500f4dd",
"weights": "7e12ddffbd1bbe89e4acdf984b9383e927f53640ef138dddd39a9373473b57c7"
} | ch-0006 | {
"data": "4a04ce3635047b2872552b4de8bd6069ec38404eed7f137938082da21c5a9180",
"prompt": "658785c4b2b4e99b895c386a8c22eddb379229314934fa86b4a02c0c4560aacc",
"tools": "ae8540f1997880ea791e454ca1de5c83423630b1da5fe1412825d92df500f4dd",
"weights": "7e12ddffbd1bbe89e4acdf984b9383e927f53640ef138dddd39a9373473b57c7"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"tools"
] | [
{
"component": "tools",
"magnitude": null
}
] | {
"data": "8e5b53c075ca0fdf4ce2eaf4cfcd4447d3463c274c15ac591127c72783a0c8c1",
"prompt": "2e2df988b11f0b93cada853345be5be27c1ca603e70cdf1344b3ef5ee7fbfa13",
"tools": "64758845ddf2c62bf297211d561625211cd33aee045b8b77cb61ffdb805539ef",
"weights": "d1ba5c18290afa93ec2438e013b966ddc3129e0f26ba14242dea31c8a07e7206"
} | ch-0007 | {
"data": "8e5b53c075ca0fdf4ce2eaf4cfcd4447d3463c274c15ac591127c72783a0c8c1",
"prompt": "2e2df988b11f0b93cada853345be5be27c1ca603e70cdf1344b3ef5ee7fbfa13",
"tools": "96514da7a28e676e092737801f60e52d3ff8f8b63776b6647a5945e6a0303b3a",
"weights": "d1ba5c18290afa93ec2438e013b966ddc3129e0f26ba14242dea31c8a07e7206"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"tools"
] | [
{
"component": "tools",
"magnitude": null
}
] | {
"data": "8a0439eb6ea6ec9007a86b900661dd1b5e02dd724b839b33d1899e1990a3dc74",
"prompt": "617a8bf8622f7537f5235daea9d5bad30a99e379f6d399d136ab0a6bf814c71b",
"tools": "bfba845f6738bdf3b1ff196a7e957b3b43c548b1fb171d8ba47dd1a8afc673b8",
"weights": "b2621f3cbce9830aa7d6cbfadd2a4a38145ac9e63eec58d3383e09edb8091d48"
} | ch-0008 | {
"data": "8a0439eb6ea6ec9007a86b900661dd1b5e02dd724b839b33d1899e1990a3dc74",
"prompt": "617a8bf8622f7537f5235daea9d5bad30a99e379f6d399d136ab0a6bf814c71b",
"tools": "ce0bd18426134091c998a1b49cdadfe80e609757afb3397ff59fc7a1d42e8a7c",
"weights": "b2621f3cbce9830aa7d6cbfadd2a4a38145ac9e63eec58d3383e09edb8091d48"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"data",
"prompt",
"tools"
] | [
{
"component": "data",
"magnitude": null
},
{
"component": "prompt",
"magnitude": null
},
{
"component": "tools",
"magnitude": null
}
] | {
"data": "15923df182f362ea127b78ec7e208bbe99df0efb20508e4e4059dfa7823d4cd9",
"prompt": "23c0c5a7da580a74c1ef2c45fc0d68c1b7dce7ae9c87d7d375cbed5ef68cc646",
"tools": "56c3b388eca90a0ec9c9a73b45d366f6d6a4692e9eb2f852a871a89775135ebc",
"weights": "4eb0d9656c501273c8c6a21c145fe41b12789e688babe13cd95a0423360e3009"
} | ch-0009 | {
"data": "538123c470f77c41191467b360c83a93cb05cd5ff66f47d3de4bb2ae2f770bf3",
"prompt": "af5b86ac1d777df6e5773ed6c65f750ee6b9dfcf3629d4704425b25d64b70c95",
"tools": "a34a2965d451b5b260ddf08f3fc5ab1b8679f3b7e59ac439fa1a67898be196a2",
"weights": "4eb0d9656c501273c8c6a21c145fe41b12789e688babe13cd95a0423360e3009"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"data",
"tools",
"weights"
] | [
{
"component": "data",
"magnitude": null
},
{
"component": "tools",
"magnitude": null
},
{
"component": "weights",
"magnitude": {
"est": 0.0044,
"true": 0
}
}
] | {
"data": "39f650fdf4eb840770368a19969a2d7453b1da858d10c1c4c0fdc65470eeada6",
"prompt": "a8cbedc1ba6fc30111c7e8d48683f69ebfd50136e04507b82dfbee2f4512475f",
"tools": "5680a58e5b728721524e1acd9c1a9ac97a8d38b646d38197fd864b0846d1043d",
"weights": "632ef660d2a9207744b268c99cd30e0db6aa80526d5dc634ba9aa804a6a1a856"
} | ch-0010 | {
"data": "b431cb0fc6b71a77fd5390ee0e6b600869d2f18374d00d1c8c3932d04ddb1c3b",
"prompt": "a8cbedc1ba6fc30111c7e8d48683f69ebfd50136e04507b82dfbee2f4512475f",
"tools": "7653c91b3796f56f251f5afd11baa20a51abe4f7dfb0e9f75804832a3c94e6f1",
"weights": "8a2d754f8b488ed12c062f07dfbe42270e997e8600d00a7a1da5e60edffcfc06"
} | {
"allowed": [
{
"component": "prompt",
"policy": "any_change"
},
{
"component": "weights",
"max_fraction": 0.05,
"policy": "bounded_magnitude"
}
]
} | true |
[
"prompt"
] | [
{
"component": "prompt",
"magnitude": null
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End of preview.
PassportBench
A signed, four-jurisdiction regulatory passport that fail-closes agent deployment on any out-of-PCCP change.
PassportBench is the benchmark corpus for The Regulatory Passport: Lifecycle and Change-Control Automation for Clinical AI Agents, the qupassport module of the QUOKKAGUARD program. It ships with the qupassport repository, which contains the qfire gateway layer under test, the experiment harness, and the paper.
150 synthetic agent passports (140 clear-stratum, 10 boundary-stratum) with author-encoded ground-truth risk/autonomy labels under FDA, EU AI Act, Health Canada, and MHRA, plus 400 paired change-events (334 out-of-envelope, 66 in-envelope) carrying deployed/live per-component SHA-256 fingerprints, PCCP, and noisy weight-magnitude estimates, with a JSON-Schema PCCP schema and 3 example plans; seed 42, stdlib-only, no PHI.
All data are synthetic. No real patient data or protected health information (PHI) is included; clinical content is generated from templates with fixed seeds.
Files
| File | Size | Rows |
|---|---|---|
README.md |
4 KB | |
changes/changes.jsonl |
393 KB | 400 rows |
passports/passports.jsonl |
85 KB | 150 rows |
pccp/examples.jsonl |
303 B | 3 rows |
pccp/schema.json |
857 B |
Record schemas
changes/changes.jsonl:changed_components,deltas,deployed_fingerprint,id,live_fingerprint,pccp,true_out_of_envelopepassports/passports.jsonl:id,labels,metadata,stratumpccp/examples.jsonl:allowed,name
How it was generated
The corpus is produced by the generator in the paper repository and is fully deterministic (fixed seeds), so it can be regenerated byte-for-byte.
# from the qupassport repository root (deterministic seeds)
python3 scripts/012-passport/gen_passports.py
Intended use
Evaluating the lifecycle enforcement layer of a clinical-agent security gateway (HAARF control C1/C6): A clinical AI agent is cleared at a specific risk class and autonomy level under a Predetermined Change Control Plan (PCCP), then silently drifts as prompts are edited, models swapped, tools added, and data refreshed.
The experiments that consume it (E-series in the paper) are reproduced from the repository:
git clone https://github.com/quome-cloud/qupassport
cd qupassport
cargo build --release
then follow the Reproduce the experiments section of its README.
Citation
This benchmark was built to evaluate a control of the Healthcare AI Agents Regulatory Framework (HAARF), the source framework for the QUOKKAGUARD program. Please cite both the paper and HAARF:
@unpublished{schwoebel2026qupassport,
author = {{QUOKKAGUARD Project}},
title = {The Regulatory Passport: Lifecycle and Change-Control Automation for Clinical AI Agents},
note = {Preprint. Quome, QUOKKAGUARD program (qupassport module)},
year = {2026},
url = {https://github.com/quome-cloud/qupassport}
}
@unpublished{schwoebel2026haarf,
author = {Schwoebel, Jim and Frasch, Martin and Spalding, Art and Sewell, Ed and Englert, Phil and Halpert, Ben and Overbay, Collin and Semenec, Ingrida and Shor, Joel},
title = {{HAARF}: Healthcare {AI} agents regulatory framework --- a comprehensive security verification standard for autonomous {AI} systems in clinical environments},
note = {medRxiv Preprint},
year = {2026},
month = {April},
doi = {10.64898/2026.04.09.26350519},
url = {https://www.medrxiv.org/content/10.64898/2026.04.09.26350519v1}
}
License
Apache License 2.0. Copyright (c) 2026 Quome, Inc.
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